Patrones y procesos espaciales en poblaciones y comunidades vegetales: nuevas herramientas e hipótesis

Generalmente los patrones espaciales de puntos en ecología, se definen en el espacio bi-dimensional, donde cada punto representado por el par ordenado (x,y), resume la ubicación espacial de una planta. La importancia de los patrones espaciales de plantas radica en que proceden como respuesta ante importantes procesos ecológicos asociados a la estructura de una población o comunidad. Tales procesos incluyen fenómenos como la dispersión de semillas, la competencia por recursos, la facilitación, respuesta de las plantas ante algún tipo de estrés, entre otros. En esta tesis se evalúan los factores y potenciales procesos subyacentes, que explican los patrones de distribución espacial de la biodiversidad vegetal en diferentes ecosistemas como bosque mediterráneo, bosque tropical y matorral seco tropical; haciendo uso de nuevas metodologías para comprobar hipótesis relacionadas a los procesos espaciales. En este trabajo se utilizaron dos niveles ecológicos para analizar los procesos espaciales, el nivel de población y el nivel de comunidad, con el fin de evaluar la importancia relativa de las interacciones intraespecíficas e interespecíficas. Me centré en el uso de funciones estadísticas que resumen los patrones de puntos para explorar y hacer inferencias a partir de datos espaciales, empezando con la construcción de un nuevo modelo nulo para inferir variantes del síndrome de dispersión de una planta parásita en España central. Se analizó la dependencia de los patrones espaciales tanto de los hospedantes afectados como de los no-afectados y se observó fuerte dependencia a pequeña y mediana distancia. Se utilizaron dos funciones (kernel) para simular la dispersión de la especie parásita y se identificó consistencia de estos modelos con otros síndromes de dispersión adicionalmente a la autodispersión. Un segundo tema consistió en desarrollar un método ANOVA de dos vías? para patrones de puntos replicados donde el interés se concentró en evaluar la interacción de dos factores. Este método se aplicó a un caso de estudio que consitió en analizar la influencia de la topografía y la altitud sobre el patrón espacial de un arbusto dominante en matorral seco al sur del Ecuador, cuyos datos provienen de patrones de puntos replicados basados en diseño. Partiendo de una metodología desarrollada para procesos uni-factoriales, se construyó el método para procesos bi-factoriales y así poder evaluar el efecto de interacción. Se observó que la topografía por sí sola así como la interacción con la altitud presentaron efecto significativo sobre la formación del patrón espacial. Un tercer tema fue identificar la relación entre el patrón espacial y el síndrome de dispersión de la comunidad vegetal en el bosque tropical de la Isla de Barro Colorado (BCI), Panamá. Muchos estudios se han desarrollado en este bosque tropical y algunos han analizado la relación síndrome-patrón espacial, sin embargo lo novedoso de nuestro estudio es que se evaluaron un conjunto amplio de modelos (114 modelos) basados en procesos que incorporan la limitación de la dispersión y la heterogeneidad ambiental, y evalúan el efecto único y el efecto conjunto, para posteriormente seleccionar el modelo de mejor ajuste para cada especie. Más de la mitad de las especies presentaron patrón espacial consistente con el efecto conjutno de la limitación de la dispersión y heterogeneidad ambiental y el porcentaje restante de especies reveló en forma equitativa el efecto único de la heterogeneidad ambiental y efecto único de limitación de la dispersión. Finalmente, con la misma información del bosque tropical de BCI, y para entender las relaciones que subyacen para mantener el equilibrio de la biodiversidad, se desarrolló un índice de dispersión funcional local a nivel de individuo, que permita relacionar el patrón espacial con cuatro rasgos funcionales clave de las especies. Pese a que muchos estudios realizados involucran esta comunidad con la teoría neutral, se encontró que el ensamble de la comunidad de BCI está afectado por limitaciones de similaridad y de hábitat a diferentes escalas. ABSTRACT Overall the spatial point patterns in ecology are defined in two-dimensional space, where each point denoted by the (x,y) ordered pair, summarizes the spatial location of a plant. The spatial point patterns are essential because they arise in response to important ecological processes, associated with the structure of a population or community. Such processes include phenomena as seed dispersal, competition for resources, facilitation, and plant response to some type of stress, among others. In this thesis, some factors and potential underlying processes were evaluated in order to explain the spatial distribution patterns of plant biodiversity. It was done in different ecosystems such as Mediterranean forest, tropical forest and dry scrubland. For this purpose new methodologies were used to test hypothesis related to spatial processes. Two ecological levels were used to analyze the spatial processes, at population and community levels, in order to assess the relative importance of intraspecific and interspecific interactions. I focused on the use of spatial statistical functions to summarize point patterns to explore and make inferences from spatial data, starting with the construction of a new null model to infer variations about the dispersal syndrome of a parasitic plant in central Spain. Spatial dependence between point patterns in a multivariate point process of affected and unaffected hosts were analyzed and strong dependence was observed at small and medium distance. Two kernel functions were used to simulate the dispersion of parasitic plant and consistency of these models with other syndromes was identified, in addition to ballistic dispersion. A second issue was to analyze altitude and topography effects on the spatial population structure of a dominant shrub in the dry ecosystem in southern Ecuador, whose data come from replicated point patterns design-based. Based on a methodology developed for uni-factorial process, a method for bi-factorial processes was built to assess the interaction effect. The topography alone and interacting with altitude showed significant effect on the spatial pattern of shrub. A third issue was to identify the relationship between the spatial pattern and dispersal syndromes of plant community in the tropical forest of Barro Colorado Island (BCI), Panamá. Several studies have been developed in this tropical forest and some focused on the spatial pattern-syndrome relationship; however the novelty of our study is that a large set of models (114 models) including dispersal limitation and environmental heterogeneity were evaluated, used to identify the only and joint effect to subsequently select the best fit model for each species. Slightly more than fifty percent of the species showed spatial pattern consistent with only the dispersal limitation, and the remaining percentage of species revealed the only effect of environmental heterogeneity and habitat-dispersal limitation joined effect, equitably. Finally, with the same information from the tropical forest of BCI, and to understand the relationships underlying for balance of biodiversity, an index of the local functional dispersion was developed at the individual level, to relate the spatial pattern with four key functional traits of species. Although many studies involve this community with neutral theory, the assembly of the community is affected by similarity and habitat limitations at different scales.

Bathymetric Terrain Model of the Puerto Rico Trench and the Northeastern Caribbean Region for Marine Geological Investigations

Multibeam bathymetric data collected in the Puerto Rico Trench and northeastern Caribbean region are compiled into a seamless bathymetric terrain model for broad-scale geological investigations of the trench system. These data, collected during eight separate surveys between 2002 and 2013 and covering almost 180,000 square kilometers, are published here in large-format map sheet and digital spatial data. This report describes the common multibeam data collection and processing methods used to produce the bathymetric terrain model and corresponding data-source polygon. Details documenting the complete provenance of the data are provided in the metadata in the Data Catalog section.

A software tool for accurate assessment of costs and CO2 emissions in wood transport using OpenStreetMap©

Costs and environmental impacts are key elements in forest logistics and they must be integrated in forest decision-making. The evaluation of transportation fuel costs and carbon emissions depend on spatial and non-spatial data but in many cases the former type of data are dicult to obtain. On the other hand, the availability of software tools to evaluate transportation fuel consumption as well as costs and emissions of carbon dioxide is limited. We developed a software tool that combines two empirically validated models of truck transportation using Digital Elevation Model (DEM) data and an open spatial data tool, specically OpenStreetMap©. The tool generates tabular data and spatial outputs (maps) with information regarding fuel consumption, cost and CO2 emissions for four types of trucks. It also generates maps of the distribution of transport performance indicators (relation between beeline and real road distances). These outputs can be easily included in forest decision-making support systems. Finally, in this work we applied the tool in a particular case of forest logistics in north-eastern Portugal

Characteristics of soil profiles from the Ouémé Upper Catchment (HVO), Térou, Benin

Soil degradation threatens agricultural production and food security in Sub-Saharan Africa. In the coming decades, soil degradation, in particular soil erosion, will become worse through the expansion of agriculture into savannah and forest and changes in climate. This study aims to improve the understanding of how land use and climate change affect the hydrological cycle and soil erosion rates at the catchment scale. We used the semi-distributed, time-continuous erosion model SWAT (Soil Water Assessment Tool) to quantify runoff processes and sheet and rill erosion in the Upper Ouémé River catchment (14500 km**2, Central Benin) for the period 1998-2005. We could then evaluate a range of land use and climate change scenarios with the SWAT model for the period 2001-2050 using spatial data from the land use model CLUE-S and the regional climate model REMO. Field investigations were performed to parameterise a soil map, to measure suspended sediment concentrations for model calibration and validation and to characterise erosion forms, degraded agricultural fields and soil conservation practices. Modelling results reveal current "hotspots" of soil erosion in the north-western, eastern and north-eastern parts of the Upper Ouémé catchment. As a consequence of rapid expansion of agricultural areas triggered by high population growth (partially caused by migration) and resulting increases in surface runoff and topsoil erosion, the mean sediment yield in the Upper Ouémé River outlet is expected to increase by 42 to 95% by 2025, depending on the land use scenario. In contrast, changes in climate variables led to decreases in sediment yield of 5 to 14% in 2001-2025 and 17 to 24% in 2026-2050. Combined scenarios showed the dominance of land use change leading to changes in mean sediment yield of -2 to +31% in 2001-2025. Scenario results vary considerably within the catchment. Current "hotspots" of soil erosion will aggravate, and a new "hotspot" will appear in the southern part of the catchment. Although only small parts of the Upper Ouémé catchment belong to the most degraded zones in the country, sustainable soil and plant management practices should be promoted in the entire catchment. The results of this study can support planning of soil conservation activities in Benin.

A broad-scale analysis of links between coastal fisheries production and mangrove extent: A case-study for northeastern Australia

The paradigm that mangroves are critical for sustaining production in coastal fisheries is widely accepted, but empirical evidence has been tenuous. This study showed that links between mangrove extent and coastal fisheries production could be detected for some species at a broad regional scale (1000s of kilometres) on the east coast of Queensland, Australia. The relationships between catch-per-unit-effort for different commercially caught species in four fisheries (trawl, line, net and pot fisheries) and mangrove characteristics, estimated from Landsat images were examined using multiple regression analyses. The species were categorised into three groups based on information on their life history characteristics, namely mangrove-related species (banana prawns Penaeus merguiensis, mud crabs Scylla serrata and barramundi Lates calcarifer), estuarine species (tiger prawns Penaeus esculentus and Penaeus semisulcatus, blue swimmer crabs Portunus pelagicus and blue threadfin Eleutheronema tetradactylum) and offshore species (coral trout Plectropomus spp.). For the mangrove-related species, mangrove characteristics such as area and perimeter accounted for most of the variation in the model; for the non-mangrove estuarine species, latitude was the dominant parameter but some mangrove characteristics (e.g. mangrove perimeter) also made significant contributions to the models. In contrast, for the offshore species, latitude was the dominant variable, with no contribution from mangrove characteristics. This study also identified that finer scale spatial data for the fisheries, to enable catch information to be attributed to a particular catchment, would help to improve our understanding of relationships between mangroves and fisheries production. (C) 2005 Elsevier B.V. All rights reserved.

Adding constrained discontinuities to Gaussian process models of wind fields

Gaussian Processes provide good prior models for spatial data, but can be too smooth. In many physical situations there are discontinuities along bounding surfaces, for example fronts in near-surface wind fields. We describe a modelling method for such a constrained discontinuity and demonstrate how to infer the model parameters in wind fields with MCMC sampling.

Adding constrained discontinuities to Gaussian process models of wind fields

Gaussian Processes provide good prior models for spatial data, but can be too smooth. In many physical situations there are discontinuities along bounding surfaces, for example fronts in near-surface wind fields. We describe a modelling method for such a constrained discontinuity and demonstrate how to infer the model parameters in wind fields with MCMC sampling.

Modeling geometric rules in object based models:an XML / GML approach

Most object-based approaches to Geographical Information Systems (GIS) have concentrated on the representation of geometric properties of objects in terms of fixed geometry. In our road traffic marking application domain we have a requirement to represent the static locations of the road markings but also enforce the associated regulations, which are typically geometric in nature. For example a give way line of a pedestrian crossing in the UK must be within 1100-3000 mm of the edge of the crossing pattern. In previous studies of the application of spatial rules (often called 'business logic') in GIS emphasis has been placed on the representation of topological constraints and data integrity checks. There is very little GIS literature that describes models for geometric rules, although there are some examples in the Computer Aided Design (CAD) literature. This paper introduces some of the ideas from so called variational CAD models to the GIS application domain, and extends these using a Geography Markup Language (GML) based representation. In our application we have an additional requirement; the geometric rules are often changed and vary from country to country so should be represented in a flexible manner. In this paper we describe an elegant solution to the representation of geometric rules, such as requiring lines to be offset from other objects. The method uses a feature-property model embraced in GML 3.1 and extends the possible relationships in feature collections to permit the application of parameterized geometric constraints to sub features. We show the parametric rule model we have developed and discuss the advantage of using simple parametric expressions in the rule base. We discuss the possibilities and limitations of our approach and relate our data model to GML 3.1. © 2006 Springer-Verlag Berlin Heidelberg.

A flexible, extensible object oriented real-time near photorealistic visualization system:the system framework design

In this paper we describe a novel, extensible visualization system currently under development at Aston University. We introduce modern programming methods, such as the use of data driven programming, design patterns, and the careful definition of interfaces to allow easy extension using plug-ins, to 3D landscape visualization software. We combine this with modern developments in computer graphics, such as vertex and fragment shaders, to create an extremely flexible, extensible real-time near photorealistic visualization system. In this paper we show the design of the system and the main sub-components. We stress the role of modern programming practices and illustrate the benefits these bring to 3D visualization. © 2006 Springer-Verlag Berlin Heidelberg.

INTAMAP: an interoperable automated interpolation web service

INTAMAP is a web processing service for the automatic interpolation of measured point data. Requirements were (i) using open standards for spatial data such as developed in the context of the open geospatial consortium (OGC), (ii) using a suitable environment for statistical modelling and computation, and (iii) producing an open source solution. The system couples the 52-North web processing service, accepting data in the form of an observations and measurements (O&M) document with a computing back-end realized in the R statistical environment. The probability distribution of interpolation errors is encoded with UncertML, a new markup language to encode uncertain data. Automatic interpolation needs to be useful for a wide range of applications and the algorithms have been designed to cope with anisotropies and extreme values. In the light of the INTAMAP experience, we discuss the lessons learnt.

Spatially structured cognitve models of semantic information:the implications for computerised databases

Existing theories of semantic cognition propose models of cognitive processing occurring in a conceptual space, where ‘meaning’ is derived from the spatial relationships between concepts’ mapped locations within the space. Information visualisation is a growing area of research within the field of information retrieval, and methods for presenting database contents visually in the form of spatial data management systems (SDMSs) are being developed. This thesis combined these two areas of research to investigate the benefits associated with employing spatial-semantic mapping (documents represented as objects in two- and three-dimensional virtual environments are proximally mapped dependent on the semantic similarity of their content) as a tool for improving retrieval performance and navigational efficiency when browsing for information within such systems. Positive effects associated with the quality of document mapping were observed; improved retrieval performance and browsing behaviour were witnessed when mapping was optimal. It was also shown using a third dimension for virtual environment (VE) presentation provides sufficient additional information regarding the semantic structure of the environment that performance is increased in comparison to using two-dimensions for mapping. A model that describes the relationship between retrieval performance and browsing behaviour was proposed on the basis of findings. Individual differences were not found to have any observable influence on retrieval performance or browsing behaviour when mapping quality was good. The findings from this work have implications for both cognitive modelling of semantic information, and for designing and testing information visualisation systems. These implications are discussed in the conclusions of this work.

INTAMAP: the design and implementation of an interoperable automated interpolation web service

INTAMAP is a Web Processing Service for the automatic spatial interpolation of measured point data. Requirements were (i) using open standards for spatial data such as developed in the context of the Open Geospatial Consortium (OGC), (ii) using a suitable environment for statistical modelling and computation, and (iii) producing an integrated, open source solution. The system couples an open-source Web Processing Service (developed by 52°North), accepting data in the form of standardised XML documents (conforming to the OGC Observations and Measurements standard) with a computing back-end realised in the R statistical environment. The probability distribution of interpolation errors is encoded with UncertML, a markup language designed to encode uncertain data. Automatic interpolation needs to be useful for a wide range of applications and the algorithms have been designed to cope with anisotropy, extreme values, and data with known error distributions. Besides a fully automatic mode, the system can be used with different levels of user control over the interpolation process.

AstroWeb – A Graphical Representation of an Astronomical WFPDB Database Using a Web-Based Open Source Geographical Information System

ACM Computing Classification System (1998): H.5.2, H.2.8, J.2, H.5.3.

Improved Annual Average Daily Traffic (AADT) estimation for local roads using parcel-level travel demand modeling

Annual Average Daily Traffic (AADT) is a critical input to many transportation analyses. By definition, AADT is the average 24-hour volume at a highway location over a full year. Traditionally, AADT is estimated using a mix of permanent and temporary traffic counts. Because field collection of traffic counts is expensive, it is usually done for only the major roads, thus leaving most of the local roads without any AADT information. However, AADTs are needed for local roads for many applications. For example, AADTs are used by state Departments of Transportation (DOTs) to calculate the crash rates of all local roads in order to identify the top five percent of hazardous locations for annual reporting to the U.S. DOT. ^ This dissertation develops a new method for estimating AADTs for local roads using travel demand modeling. A major component of the new method involves a parcel-level trip generation model that estimates the trips generated by each parcel. The model uses the tax parcel data together with the trip generation rates and equations provided by the ITE Trip Generation Report. The generated trips are then distributed to existing traffic count sites using a parcel-level trip distribution gravity model. The all-or-nothing assignment method is then used to assign the trips onto the roadway network to estimate the final AADTs. The entire process was implemented in the Cube demand modeling system with extensive spatial data processing using ArcGIS. ^ To evaluate the performance of the new method, data from several study areas in Broward County in Florida were used. The estimated AADTs were compared with those from two existing methods using actual traffic counts as the ground truths. The results show that the new method performs better than both existing methods. One limitation with the new method is that it relies on Cube which limits the number of zones to 32,000. Accordingly, a study area exceeding this limit must be partitioned into smaller areas. Because AADT estimates for roads near the boundary areas were found to be less accurate, further research could examine the best way to partition a study area to minimize the impact.^

Space-for-Time Substitution Works in Everglades Ecological Forecasting Models

Space-for-time substitution is often used in predictive models because long-term time-series data are not available. Critics of this method suggest factors other than the target driver may affect ecosystem response and could vary spatially, producing misleading results. Monitoring data from the Florida Everglades were used to test whether spatial data can be substituted for temporal data in forecasting models. Spatial models that predicted bluefin killifish (Lucania goodei) population response to a drying event performed comparably and sometimes better than temporal models. Models worked best when results were not extrapolated beyond the range of variation encompassed by the original dataset. These results were compared to other studies to determine whether ecosystem features influence whether space-for-time substitution is feasible. Taken in the context of other studies, these results suggest space-for-time substitution may work best in ecosystems with low beta-diversity, high connectivity between sites, and small lag in organismal response to the driver variable.